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Optimization of water-energy nexus in shale gas exploration: From production to transmission

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  • Oke, Doris
  • Mukherjee, Rajib
  • Sengupta, Debalina
  • Majozi, Thokozani
  • El-Halwagi, Mahmoud M.

Abstract

This work presents a mathematical framework for optimizing water-energy nexus during shale gas production, processing, distribution, usage in power generation, and transmission of produced power. The framework entails a superstructure-based mathematical formulation. Regeneration is achieved using membrane distillation (MD), whereby the treated water can be reused at the next fracturing operation. The developed model incorporates a detailed design model of MD to account for the design specifications and energy requirements of the water regenerator. Hence, water, energy, operating and/or capital cost are optimized simultaneously. The study considers natural gas as fuel for commercial, industrial and residential customers, as well as for electric power generation, with the goal of maximizing the overall profit. The resultant model is applied to a case study, which is a representative of Marcellus shale play. The approach results in 23.2% reduction in freshwater utilization, 18.6% reduction in the freshwater cost and 42.7% reduction in the energy requirement of the regenerator. The energy requirement for regeneration is 160 × 103 kJ/m3 of water. The results indicate that the cost incurred in the network involving wet gas is 41.76% higher than the network involving dry gas due to the processing requirement of wet gas.

Suggested Citation

  • Oke, Doris & Mukherjee, Rajib & Sengupta, Debalina & Majozi, Thokozani & El-Halwagi, Mahmoud M., 2019. "Optimization of water-energy nexus in shale gas exploration: From production to transmission," Energy, Elsevier, vol. 183(C), pages 651-669.
    • Handle: RePEc:eee:energy:v:183:y:2019:i:c:p:651-669
    DOI: 10.1016/j.energy.2019.06.104
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    References listed on IDEAS

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    1. Shih, Jhih-Shyang & Swiedler, Elaine & Krupnick, Alan, 2016. "A Model for Shale Gas Wastewater Management," RFF Working Paper Series dp-16-44, Resources for the Future.
    2. Chen, Yizhong & He, Li & Li, Jing, 2017. "Stochastic dominant-subordinate-interactive scheduling optimization for interconnected microgrids with considering wind-photovoltaic-based distributed generations under uncertainty," Energy, Elsevier, vol. 130(C), pages 581-598.
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    Cited by:

    1. Fadhil Y. Al-Aboosi & Mahmoud M. El-Halwagi, 2019. "A Stochastic Optimization Approach to the Design of Shale Gas/Oil Wastewater Treatment Systems with Multiple Energy Sources under Uncertainty," Sustainability, MDPI, vol. 11(18), pages 1-39, September.
    2. Oke, Doris & Mukherjee, Rajib & Sengupta, Debalina & Majozi, Thokozani & El-Halwagi, Mahmoud, 2020. "On the optimization of water-energy nexus in shale gas network under price uncertainties," Energy, Elsevier, vol. 203(C).
    3. Cong Chen & Lei Yu & Xueting Zeng & Guohe Huang & Yongping Li, 2020. "Planning an Energy–Water–Environment Nexus System in Coal-Dependent Regions under Uncertainties," Energies, MDPI, vol. 13(1), pages 1-40, January.

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